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Abstract

Background

Stroke onset demonstrates a circadian pattern, but the relationship between onset time and stroke severity at admission remains insufficiently understood.

Objectives

This study aimed to examine the association between time of stroke onset and admission severity in patients with acute ischemic stroke (AIS), and to determine whether this association varies across clinical subgroups.

Design

A retrospective observational study.

Methods

We conducted a multicenter retrospective cohort study including 14,048 patients diagnosed with AIS and admitted to 36 hospitals in Shenzhen, China, between January 1, 2022, and May 31, 2024. Stroke onset time was classified into 4 periods: Morning (05:00-10:59), Afternoon (11:00-16:59), Evening (17:00-22:59), and Night (23:00-04:59). The primary outcome was neurological severity at admission, measured by the NIHSS score. Associations between onset time and outcomes were evaluated using multivariable ordinal logistic and linear regression models, adjusted for demographic and clinical covariates. Subgroup analyses and sensitivity analyses using multiple imputation were also conducted.

Results

Stroke onset in the Morning was associated with lower NIHSS scores (adjusted odds ratio [aOR] = 0.88; 95% confidence interval [CI]: 0.82-0.94; P < .001) and lower mRS scores (aOR = 0.81; 95% CI: 0.76-0.86; P < .001). In contrast, Night onset was associated with higher NIHSS scores (aOR = 1.20; 95% CI: 1.09-1.32; P < .001) and mRS scores (aOR = 1.25; 95% CI: 1.15-1.37; P < .001). These associations were consistent across strata defined by age and sex, and among patients with hypertension or diabetes. However, the circadian pattern was attenuated in patients with coronary artery disease, dyslipidemia, or atrial fibrillation.

Conclusion

Admission stroke severity follows a circadian pattern, with milder presentations in the Morning and more severe impairments during Night hours. These findings highlight the potential role of circadian biology in stroke pathophysiology and support incorporating time-of-onset considerations into clinical risk stratification and acute management strategies.

Plain Language Summary

Background

How circadian rhythms influence the severity of acute ischemic stroke remains unclear.

Methods

A retrospective cohort study was conducted involving 14,048 AIS patients from 36 hospitals in Shenzhen between January 2022 and May 2024. Onset time was grouped into four categories: Morning, Afternoon, Evening, and Night. The primary outcome was admission National Institutes of Health Stroke Scale score. Data were analyzed using multivariable regression, subgroup analyses, and sensitivity tests.

Results

Morning onset was associated with lower NIHSS scores (aOR 0.88) and modified Rankin Scale scores (aOR 0.81). Night onset was associated with higher NIHSS scores (aOR 1.20) and mRS scores (aOR 1.25). This pattern was consistent across different age, sex, hypertension, and diabetes mellitus subgroups but was less pronounced in patients with coronary artery disease, dyslipidemia, and atrial fibrillation.

Conclusions

Admission severity of AIS follows a circadian rhythm, with milder severity in the morning and worse severity at night. These findings suggest that circadian biology may be involved in the pathophysiology of AIS.

Keywords

acute ischemic stroke stroke onset time stroke severity circadian rhythm NIHSS

Introduction

Stroke onset follows a well-established circadian rhythm, and is not evenly distributed throughout the day. The incidence of acute ischemic stroke (AIS) peaks in the early morning hours (approximately 05:00-12:00),^1-6 with a secondary, smaller peak often observed in the late afternoon to early evening.^1,7,8

Beyond influencing incidence, onset timing may also affect clinical severity, neurological deterioration, and long-term outcomes.^6,9-11 In a cohort study of 17,461 patients with AIS, Ryu et al reported that strokes occurring at night were associated with higher National Institutes of Health Stroke Scale (NIHSS) scores at admission, increased incidence of early neurological deterioration (END), and poorer 3-month functional outcomes.⁹ Similarly, Ripamonti et al observed that strokes occurring during sleep were linked to worse discharge outcomes, including higher modified Rankin Scale (mRS) scores and a 33% increased risk of 1-month mortality, particularly among patients with the cardioembolism subtype.⁶

Although previous studies have suggested potential associations between stroke onset time and disease severity or outcomes, comprehensive evaluations of the relationship between time-of-day onset and neurological severity at presentation remain limited. Furthermore, few studies have systematically evaluated this question across clinical subgroups or stroke subtypes. Therefore, the primary objective of this study was to investigate the association between time of stroke onset and admission severity in a large, multicenter cohort of patients with AIS. We further aimed to explore whether this association varies by age, sex, vascular risk factors, and stroke subtype. These findings may offer novel insights into the role of circadian biology in stroke pathogenesis and inform time-sensitive strategies in stroke triage and care.

Materials and Methods

Study Design and Population

This retrospective, multicenter cohort study was conducted at 36 hospitals in Shenzhen, China. All participating centers were part of the Shenzhen Cerebrovascular Disease Treatment Quality Control Network. The study was approved by the ethics committee of the Shenzhen Cerebrovascular Disease Treatment and Quality Control Center. Informed consent was waived due to the retrospective design.

We included consecutive patients aged ≥18 years who were diagnosed with AIS and admitted between January 1, 2022, and May 31, 2024. A total of 35,011 patients with AIS were initially screened. Eligible patients were those admitted within 24 hours of symptom onset, with a clearly documented time of stroke onset and a documented NIHSS score at admission, and without predefined exclusion criteria. Of these, 14,463 patients were excluded due to missing onset time, 13,540 were admitted beyond the 24-hour window, and 47 lacked NIHSS score data at admission. The final analysis included 14,048 patients.

Outcomes and Time of Onset Classification

The primary outcome was neurological severity at admission, assessed using the NIHSS. For analysis, NIHSS scores were grouped into 5 severity categories: 0, 1-4, 5-15, 16-20, and ≥21.¹² The secondary outcome was functional status at admission, measured by the mRS. Both scores were routinely assessed and recorded by trained neurologists upon hospital admission as part of standard clinical practice.

Stroke onset time was defined as the moment when symptoms were first recognized by the patient or a witness. Based on this, patients were categorized into 4 onset-time groups, following the circadian classification proposed by the Leducq Network¹³: Morning (05:00-10:59), Afternoon (11:00-16:59), Evening (17:00-22:59), and Night (23:00-04:59). This classification system is designed for time-of-day analysis of circadian effects on stroke. Unless otherwise specified, each onset group was compared against all other groups combined.

Statistical Analysis

Descriptive statistics were used to summarize patient characteristics by onset time category. Continuous variables were expressed as medians and interquartile range (IQR), and categorical variables as frequencies and percentages. Group comparisons were performed using the Kruskal–Wallis test for continuous variables and the chi-square test for categorical variables.

Multivariable ordinal logistic regression was used to assess the association between stroke onset time and NIHSS and mRS scores at admission. For continuous modeling of NIHSS, multiple linear regression was applied. For binary mRS analysis (0-2 vs 3-6), binary logistic regression was used. All models were adjusted for the following covariates: age, sex, hypertension, diabetes mellitus, atrial fibrillation, coronary artery disease, dyslipidemia, prestroke mRS score, stroke subtype, current or recent smoking, and current or recent drinking.

Prespecified subgroup analyses were performed according to age (<65 vs ≥65 years), sex, vascular risk factors (hypertension, diabetes, atrial fibrillation, dyslipidemia, coronary artery disease), and TOAST stroke subtype. Effect modification was assessed by introducing interaction terms between onset time and each subgroup variable into the models.

To assess the robustness of the findings, sensitivity analyses were conducted using multiple imputation by chained equations (MICE) to account for missing data under the assumption of missing at random (MAR). Twenty imputed datasets were generated, and model estimates were pooled using Rubin’s rules.

All statistical tests were two-sided, and a P-value <.05 was considered statistically significant. All analyses were performed using R software (version 4.4.3).

Results

Baseline Characteristics and Admission Score Distribution

A total of 14,048 patients with AIS were included in the study. Based on the time of stroke onset, patients were categorized into 4 groups: Morning (05:00-10:59; n = 4,657, 33.2%), Afternoon (11:00-16:59; n = 3,938, 28.0%), Evening (17:00-22:59; n = 3,577, 25.5%), and Night (23:00-04:59; n = 1,876, 13.3%).

Baseline characteristics across the 4 onset-time groups are summarized in Table 1. The median age of the overall cohort was 59 years (IQR: 51-69), and 70.8% (n = 9944) were male. The median NIHSS score at admission was 3 (IQR: 1-6), and the median admission mRS score was 2 (IQR: 1-3).

Table 1.

Baseline Characteristics of Patients by Time of Stroke Onset

Demographic characteristics	All patients (n = 14,048)	Morning (05:00-10:59) (n = 4,657)	Afternoon (11:00-16:59) (n = 3,938)	Evening (17:00-22:59) (n = 3,577)	Night (23:00-04:59) (n = 1,876)	P-value
Age, median (IQR)	59 (51, 69)	60 (52, 70)	59 (51, 70)	59 (51, 69)	58 (50, 68)	<0.001***
Male, n (%)	9,944 (70.8%)	3,274 (70.3%)	2,758 (70.0%)	2,542 (71.1%)	1,370 (73.0%)	0.10
Admission NIHSS score, median (IQR)	3 (1, 6)	2 (1, 5)	3 (1, 5)	3 (1, 6)	3 (1, 6)	<0.001***
Admission mRS score, median (IQR)	2 (1, 3)	2 (1, 3)	2 (1, 3)	2 (1, 3)	2 (1, 4)	<0.001***
Prestroke mRS score, median (IQR)	0 (0, 1)	0 (0, 1)	0 (0, 1)	0 (0, 0)	0 (0, 1)	<0.001***
Hypertension, n (%)	5,303 (37.8%)	1,762 (37.9%)	1,486 (37.8%)	1,363 (38.1%)	692 (37.0%)	0.86
Diabetes mellitus, n (%)	2,860 (20.4%)	951 (20.5%)	796 (20.2%)	723 (20.2%)	390 (20.8%)	0.95
Atrial fibrillation, n (%)	611 (4.4%)	182 (3.9%)	171 (4.3%)	173 (4.8%)	85 (4.5%)	0.23
Coronary artery disease, n (%)	632 (4.5%)	216 (4.6%)	165 (4.2%)	169 (4.7%)	82 (4.4%)	0.66
Dyslipidemia, n (%)	1,975 (14.1%)	654 (14.1%)	512 (13.0%)	525 (14.7%)	284 (15.2%)	0.09
Current or recent smoking, n (%)	4,478 (32.0%)	1,411 (30.4%)	1,266 (32.2%)	1,199 (33.6%)	602 (32.2%)	0.02*
Current or recent drinking, n (%)	2,613 (19.1%)	834 (18.4%)	741 (19.3%)	680 (19.5%)	358 (19.6%)	0.51
Stroke subtype, n (%)						<0.001***
Large artery atherosclerosis	4,970 (35.6%)	1,680 (36.3%)	1,380 (35.2%)	1,300 (36.5%)	610 (32.8%)
Small vessel occlusion	6,448 (46.2%)	2,167 (46.8%)	1,803 (46.0%)	1,569 (44.0%)	909 (48.8%)
Cardioembolism	919 (6.6%)	269 (5.8%)	269 (6.9%)	264 (7.4%)	117 (6.3%)
Other determined etiology	872 (6.2%)	277 (6.0%)	244 (6.2%)	209 (5.9%)	142 (7.6%)
Undetermined etiology	761 (5.4%)	238 (5.1%)	220 (5.6%)	220 (6.2%)	83 (4.5%)

Abbreviations: IQR, interquartile range; NIHSS, National Institutes of Health Stroke Scale; mRS, modified Rankin Scale.

Statistical significance was indicated as follows: *P < 0.05, **P < 0.01, ***P < 0.001.

Statistically significant differences were observed in the distribution of stroke subtypes by onset time (P < .001). The proportion of large-artery atherosclerosis was lowest in the Night group (32.8%), whereas the Night group had higher proportions of small vessel occlusion (48.8%) and other determined etiology (7.6%). The Evening group had relatively higher proportions of cardioembolism (7.4%) and undetermined etiology (6.2%).

Figure 1 presents the distribution of admission NIHSS and mRS scores across onset groups. The Morning group showed lower median NIHSS score (median: 2, IQR: 1-5) compared with the Evening and Night groups (P < .01). The Night group demonstrated greater variability in mRS scores (IQR: 1-4).

Figure 1.

Distribution of admission NIHSS and mRS scores by time of stroke onset.

Multivariable Analysis of Stroke Onset Time and Admission Severity

In the ordinal logistic regression model for admission NIHSS score groups, stroke onset in the Morning group was associated with lower neurological severity (adjusted odds ratio [aOR] = 0.88; 95% CI: 0.82-0.94; P < .001), while Night onset was associated with higher severity (aOR = 1.20; 95% CI: 1.09-1.32; P < .001) (Figure 2(A)). Consistent results were observed in the multiple linear regression model: Morning onset was linked to lower NIHSS score (adjusted β = −0.35; 95% CI: −0.54 to −0.16; P < .001), whereas Night onset was linked to higher score (adjusted β = 0.46; 95% CI: 0.21 to 0.72; P < .001) (Figure 2(B)).

Figure 2.

Forest plot of multivariable analysis of the association between stroke onset time and admission NIHSS and mRS scores.

In the ordinal logistic regression analysis for admission mRS scores, Morning onset was associated with milder functional impairment (aOR = 0.81; 95% CI: 0.76-0.86; P < .001), while both Evening (aOR = 1.10; 95% CI: 1.03-1.18; P = .006) and Night onset (aOR = 1.25; 95% CI: 1.15-1.37; P < .001) were associated with higher score (Figure 2(C)). Similarly, in the binary logistic regression model (mRS 0-2 vs 3-6), Morning onset was linked to a significantly greater likelihood of favorable functional status (aOR = 1.28; 95% CI: 1.18-1.38; P < .001). Conversely, both Evening (aOR = 0.87; 95% CI: 0.80-0.95; P = .002) and Night onset (aOR = 0.78; 95% CI: 0.70-0.87; P < .001) were associated with a greater likelihood of poor functional status at admission (Figure 2(D)).

Subgroup Analyses and Multiple Imputation

The associations between stroke onset time and admission severity remained consistent across most clinical subgroups (Figure 3 and Figure S1). Among patients aged ≥65 years, Morning onset was significantly associated with lower NIHSS score (aOR = 0.82; 95% CI: 0.73-0.91; P < .001), while among those aged <65 years, Night onset was associated with higher severity (aOR = 1.25; 95% CI: 1.11-1.41; P < .001). In both male and female patients, Morning onset consistently predicted milder neurological impairment (P < .05).

Figure 3.

Subgroup analyses of the association between stroke onset time and admission NIHSS score group. Multivariable ordinal logistic regression analyses evaluating the association between stroke onset time and admission NIHSS severity across clinical subgroups. Four time-of-day onset categories are shown:

In patients with hypertension or diabetes mellitus, the circadian pattern of stroke severity remained evident—Morning onset was associated with lower NIHSS score, while Night onset was associated with higher severity. However, in patients with dyslipidemia, coronary artery disease, or atrial fibrillation, the association between onset time and stroke severity was attenuated and not statistically significant (P > .05). When stratified by stroke subtype, the circadian variation in stroke severity was primarily observed among patients with large artery atherosclerosis. Similar time-dependent patterns were also found for mRS score at admission (Table S1).

The associations between stroke onset time and admission severity remained materially unchanged after multiple imputation. In the ordinal logistic regression models, Morning onset continued to be associated with lower NIHSS scores (pooled aOR = 0.89; 95% CI: 0.83-0.96; P = .001), while Night onset was associated with higher score (pooled aOR = 1.17; 95% CI: 1.06-1.29; P = .002). Similar trends were observed in mRS analyses. These results confirmed the consistency and stability of the primary analysis conclusions (Table S1).

Discussion

In this multicenter study, we identified a significant circadian pattern in the neurological severity of AIS. Stroke onset during the Morning was associated with lower NIHSS and mRS scores, while onset during the Evening and Night was associated with greater severity. These associations persisted after adjustment for multiple confounders, and remained consistent across key subgroups, including age, sex, and vascular risk factors.

Consistent with previous reports, our study confirmed that AIS onset is most frequent during the early morning hours.^2-4 The pathophysiological mechanisms underlying the circadian variation in stroke onset are likely multifactorial. During the early morning hours, physiological changes such as a surge in blood pressure, increased sympathetic activity, enhanced platelet aggregation, blood hyperviscosity, and reduced fibrinolytic capacity contribute to a prothrombotic and vulnerable vascular state.^14-20 For instance, the abrupt rise in blood pressure and heightened sympathetic activity upon awakening are well-established contributors to atherosclerotic plaque rupture and subsequent thrombus formation.^14,21,22 During the early morning hours, platelet aggregability and blood viscosity reach their peak, coinciding with elevations in circulating catecholamines, red blood cell counts, and platelet numbers.^15,20,23,24 Concurrently, the release of nitric oxide (NO) from endothelial cells is diminished, whereas levels of vascular cell adhesion molecule-1 (VCAM-1)-positive microparticles are increased.²⁴ Moreover, a morning-specific hypofibrinolytic state has been documented, characterized by elevated levels of plasminogen activator inhibitor-1 (PAI-1) and decreased activity of tissue plasminogen activator (tPA).^24-26 In addition, circadian rhythms of hormones may also be involved. Nocturnal surges in hormones such as growth hormone and thyroid hormone, which are known to influence vascular structure and hemodynamics, could represent potential factors contributing to worsened severity during the night.²⁷ Together, these physiological, biochemical, and endocrine alterations create a prothrombotic milieu during the morning hours, which may partly explain the increased incidence of ischemic cerebrovascular events observed during this time window.

Consistent with previous findings, our study revealed that stroke severity is greater among patients with onset during the evening and night hours. Earlier research has indicated that nocturnal strokes are linked to more extensive ischemic injury, including larger infarct core and penumbral volumes, a smaller volume of salvageable tissue, and reduced leptomeningeal collateral perfusion.²⁸ Sreekrishnan et al demonstrated that leptomeningeal collateral activation is significantly diminished during the afternoon-to-evening period (15:00-22:59) compared to both the daytime (07:00-14:59) and late-night (23:00-06:59) hours, potentially contributing to larger infarct core volumes and poorer early perfusion status.²⁹ Beyond hemodynamic factors, the intrinsic state of sleep during nocturnal strokes may directly exacerbate brain injury. Sleep disruption, particularly the deprivation of rapid eye movement sleep, has been shown to compromise the integrity of the blood-brain barrier by downregulating tight junction proteins, leading to increased permeability and allowing neurotoxic substances into the brain parenchyma.³⁰

Previous studies have reported stroke subtype-specific circadian patterns in both onset timing and clinical outcomes.^9,31 For example, large-artery atherosclerosis (LAA) cases with nighttime onset have been associated with a higher incidence of END and poorer 3-month functional outcomes. In contrast, cases of cardioembolism occurring at night were associated with more severe neurological deficits at admission and similarly poor long-term outcomes. However, among patients with small vessel occlusion (SVO), no significant differences in END rates or 3-month outcomes were observed between nocturnal and daytime onset.⁹

In this study, the circadian patterns observed in the overall population remained consistent among patients with hypertension, diabetes, and LAA subtype, suggesting these groups exhibit similar time-of-day–dependent variation in stroke severity. In contrast, among patients with coronary artery disease, dyslipidemia, or atrial fibrillation, such circadian trends were attenuated or absent, indicating that additional physiological or clinical factors may modulate the relationship between onset time and stroke severity in these populations. These findings emphasize the need for further mechanistic studies to elucidate the complex interplay between circadian rhythms and stroke pathophysiology across different clinical subgroups.

Previous research suggests that stroke onset time may also influence treatment response and long-term outcomes, particularly following intravenous thrombolysis (IVT) ^32,33 or endovascular therapy (EVT).^34-37 In a study by Vilas et al, daytime administration of tPA was independently associated with higher rates of complete middle cerebral artery recanalization and better 90-day functional outcome. Specifically, treatment during daytime hours was associated with an aOR of 2.37 (95% CI: 1.02-5.52; P = .045) for complete recanalization.³³ Similarly, a study by Hajdu et al found that EVT performed in the early morning (08:00-10:20) was associated with improved 90-day outcomes.³⁶ In a cohort involving 9357 AIS patients, EVT performed during the morning period (05:00-10:59) was associated with more favorable clinical outcomes, including lower mRS scores at 90 days, higher rates of functional independence, lower mRS scores at discharge, and lower NIHSS score at 24 hours post-treatment.³⁵

Our findings underscore the potential influence of endogenous circadian rhythms on stroke pathophysiology and highlight the importance of incorporating time-of-onset considerations into clinical risk stratification and acute-phase care. Further mechanistic studies are warranted to explore the biological underpinnings of this temporal variation and to optimize time-sensitive strategies for stroke prevention and treatment.

This study has several implications for clinical practice. First, for risk stratification, identifying patients with onset during the high-risk evening and night periods could alert clinicians to a potentially more severe clinical course, prompting closer monitoring and preparedness for complications from the moment of admission. Second, in acute management, our results suggest that the underlying pathophysiology of strokes occurring during these vulnerable windows may warrant a more aggressive therapeutic approach. Finally, from a healthcare systems perspective, recognizing circadian patterns in stroke severity could inform resource allocation within stroke centers. Understanding the biological underpinnings of these temporal patterns may eventually lead to time-of-day-specific neuroprotective strategies or adjunctive treatments aimed at mitigating the more severe damage associated with nocturnal strokes.

Limitations

This study has several limitations. First, as a multicenter study conducted within a single city, our findings may have limited generalizability to populations. Second, the retrospective design may introduce information bias and limit the ability to establish causal relationships. Third, the time of stroke onset was based on self-report or witness account, which may be prone to recall bias. Fourth, to ensure precise analysis of the ‘time of onset,’ we excluded patients with an unknown onset time. Although this might introduce a selection bias, a comparison of baseline severity showed that the excluded group had a slightly lower median NIHSS score (2) than the included group (3), suggesting that our cohort did not systematically exclude more severe cases. Fifth, the use of the NIHSS as the primary severity scale is a limitation, as it is less sensitive to symptoms of posterior circulation stroke. However, the consistent findings observed with the mRS strengthen the robustness of our primary conclusions. Finally, although this study explored circadian effects across subgroups, unmeasured confounding factors—such as sleep quality, circadian misalignment, or prehospital delay—cannot be fully excluded, and mechanistic insights warrant further prospective investigation.

Conclusions

In summary, this study demonstrates that the severity of AIS at presentation follows a circadian pattern, with milder clinical manifestations in the Morning and more severe impairments during the Night hours. These associations remained consistent across key subgroups, including patients with hypertension, diabetes, and large-artery atherosclerosis, but were attenuated in those with atrial fibrillation, dyslipidemia, or coronary artery disease, suggesting differential modulation by comorbid conditions.

Supplemental Material

Supplemental Material - The Influence of Circadian Onset Time on Admission Severity in Acute Ischemic Stroke: A Retrospective Cohort Study

Supplemental Material for The Influence of Circadian Onset Time on Admission Severity in Acute Ischemic Stroke: A Retrospective Cohort Study by Shaoling Li, Shiyu Hu, Yuqi Liao, Manjuan Yao, Lijie Ren in Journal of Central Nervous System

Footnotes

Acknowledgments

We thank all the patients, study investigators, and staff involved in this study.

ORCID iD

Shaoling Li

Ethical Considerations

This study was approved by the Ethics Committee of Shenzhen Second People’s Hospital (Approval No. 20211011010-FS01).

Consent to Participate

This retrospective analysis was conducted using fully anonymized data; thus, the requirement for informed consent was waived.

Author contributions

Lijie Ren: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing – review & editing.

Shaoling Li: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft.

|Shiyu Hu: Conceptualization, Data curation, Formal analysis, Methodology, Supervision, Validation, Visualization, Writing – review & editing.

Yuqi Liao: Investigation, Methodology, Writing – original draft.

Manjuan Yao: Investigation, Methodology, Writing – original draft.

Funding

This study was supported by Noncommunicable Chronic Diseases-National Science and Technology Major Project (NO: 2023ZD0504800, 2023ZD0504802), Shenzhen Clinical Research Center for Neurological Diseases (NO: LCYSSQ20220823091204009), and Scientific Research Items of Shenzhen Science and Technology Innovation Program (NO: GJHZ20200731095602009).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data analyzed in the current study are available from the corresponding author upon reasonable request.*

Supplemental Material

Supplemental Material for this article is available online.

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